SIMPLACE offers a flexible and transparent approach to developing customized crop models
Author - Rachel Shekar
Rachel Shekar
What drives cambium development?
Using a mathematical model to test a proposed cambial cell division feedback loop.
Unlocking the secret to breeding high yielding protein-rich wheat
Models enable the optimization of multiple trait trade-offs.
Introducing Cropbox: a declarative crop modeling framework
Plant modelers do not also need to be software engineers thanks to Cropbox framework
Is photorespiration necessary for photosynthesis?
Modelling unveils the role of photorespiration in stabilizing the Calvin cycle.
How to account for clonal pup mass
Modeling differences in reproductive effort between iteroparous and semelparous reproductive strategies in Bromeliaceae
Why is active carbon storage being ignored by modelers?
Active carbon pools need to be included for accurate simulation of plant growth patterns under fluctuating environments.
Improving crop modeling using machine learning
Integration of machine learning and crop modelling can optimize predictions of plant growth and yield.
Modelling pollen competition
Identification of traits affecting pollen performance
New open source software for identifying candidate genes
Introducing cageminer, an R/Bioconductor package to prioritize candidate genes by integrating GWAS and gene coexpression networks
Simulating red:far red ratio in your model
The best method depends on your goal, need for accuracy, and computing allowance
Autonomous construction of 3D leaves
An assessment of deep generative networks in creating realistic 3D data
Machine learning used to identify transcription factor-DNA interactions
Surveying machine learning methods to improve detection of binding sites.
Modelling perennial grass phenology
Predicting phenology can provide insight into better management.
